Intercontinental Impacts of Ozone Pollution on Human Mortality
Bibliographic record
Abstract
Ozone exposure is associated with negative health impacts, including premature mortality. Observations and modeling studies demonstrate that emissions from one continent influence ozone air quality over other continents. We estimate the premature mortalities avoided from surface ozone decreases obtained via combined 20% reductions of anthropogenic nitrogen oxide, nonmethane volatile organic compound, and carbon monoxide emissions in North America (NA), EastAsia (EA), South Asia (SA), and Europe (EU). We use estimates of ozone responses to these emission changes from several atmospheric chemical transportmodels combined with a health impactfunction. Foreign emission reductions contribute approximately 30%, 30%, 20%, and >50% of the mortalities avoided by reducing precursor emissions in all regions together in NA, EA, SA and EU, respectively. Reducing emissions in NA and EU avoids more mortalities outside the source region than within, owing in part to larger populations in foreign regions. Lowering the global methane abundance by 20% reduces mortality mostin SA,followed by EU, EA, and NA. For some source-receptor pairs, there is greater uncertainty in our estimated avoided mortalities associated with the modeled ozone responses to emission changes than with the health impact function parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".